Datamining Dreams

Virtually every culture throughout history has developed methods to interpret dreams — most notably, in the modern era, the psychoanalytic approach.

Virtually every culture throughout history has developed methods to interpret dreams — most notably, in the modern era, the psychoanalytic approach.

Virtually every culture throughout history has developed methods to interpret dreams — most notably, in the modern era, the psychoanalytic approach.

This conclusion is premature.

For many years, researchers (including me) have been using quantitative methods of analysis to study the content of dreams.

Furthermore, recent advances in digital technology are expanding this approach, potentially boosting by many orders of magnitude our ability to understand the statistically recurring patterns in people’s dreams.

Furthermore, recent advances in digital technology are expanding this approach, potentially boosting by many orders of magnitude our ability to understand the statistically recurring patterns in people’s dreams.

She collected a total of 375 dream reports, each of which she analyzed and “coded” for several categories of content and then tabulated to determine which elements appeared most often.

She found, for example, that the content of these dreams was routinely characterized by realistic settings, lots of familiar characters (“the dream world is well peopled”), mostly negative emotions, a surprisingly high proportion of rational thought and a “very striking” preponderance of visual imagery compared with other sense perceptions.

She found, for example, that the content of these dreams was routinely characterized by realistic settings, lots of familiar characters (“the dream world is well peopled”), mostly negative emotions, a surprisingly high proportion of rational thought and a “very striking” preponderance of visual imagery compared with other sense perceptions.

She found, for example, that the content of these dreams was routinely characterized by realistic settings, lots of familiar characters (“the dream world is well peopled”), mostly negative emotions, a surprisingly high proportion of rational thought and a “very striking” preponderance of visual imagery compared with other sense perceptions.

She found, for example, that the content of these dreams was routinely characterized by realistic settings, lots of familiar characters (“the dream world is well peopled”), mostly negative emotions, a surprisingly high proportion of rational thought and a “very striking” preponderance of visual imagery compared with other sense perceptions.

For example, we now know that artists are more likely than non-artists to have nightmares; that children have more animals in their dreams than do adults; and that younger people are more likely than older people to have “lucid” dreams — those in which self-awareness is experienced within the dream state.

The emergence of modern digital-search technology has raised the intriguing possibility of pushing Calkins’s rather slow and labor-intensive approach to new levels of speed and sophistication.

The emergence of modern digital-search technology has raised the intriguing possibility of pushing Calkins’s rather slow and labor-intensive approach to new levels of speed and sophistication.

The emergence of modern digital-search technology has raised the intriguing possibility of pushing Calkins’s rather slow and labor-intensive approach to new levels of speed and sophistication.

What if the coding categories she and others have used could be transformed into computer algorithms that automatically analyze not just hundreds but thousands or even millions of dreams?

To take the first step in exploring that possibility I have conducted several experiments in “blind analysis,” a technique developed with the help of the psychologist G. William Domhoff at the University of California, Santa Cruz.

To take the first step in exploring that possibility I have conducted several experiments in “blind analysis,” a technique developed with the help of the psychologist G. William Domhoff at the University of California, Santa Cruz.

Without reading the narratives of the dreams, I upload the file into a computer program (and database) designed for this purpose.

Without reading the narratives of the dreams, I upload the file into a computer program (and database) designed for this purpose.

The program enables the use of a word-search template to analyze the reports.

The program enables the use of a word-search template to analyze the reports.

Then I make inferences about the person’s concerns, activities and relationships in waking life and send them to Professor Domhoff.

He forwards them to the participant, who confirms or disconfirms my conjectures.

On the contrary, they seemed the most obvious predictions that you could make given the statistical results.

On the contrary, they seemed the most obvious predictions that you could make given the statistical results.

But this is precisely the point: the fact that my conjectures were mostly right suggests that genuinely meaningful aspects of dreaming can be objectively identified using fairly simple digital methods.

How much more might a technologically enhanced system of “big data” dream analysis teach us about people’s lives?

From the American Indian ritual of the vision quest to the Muslim prayer and dream-incubation practice of istikhara, there have been cultural traditions of enhancing people’s awareness of their dreams and deriving insights from them.

From the American Indian ritual of the vision quest to the Muslim prayer and dream-incubation practice of istikhara, there have been cultural traditions of enhancing people’s awareness of their dreams and deriving insights from them.